Overview

Brought to you by YData

Dataset statistics

Number of variables34
Number of observations58913
Missing cells172147
Missing cells (%)8.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.3 MiB
Average record size in memory272.0 B

Variable types

Numeric7
DateTime4
Categorical12
Text10
Unsupported1

Alerts

agency has constant value "DOHMH" Constant
agency_name has constant value "Department of Health and Mental Hygiene" Constant
complaint_type has constant value "Food Establishment" Constant
bbl is highly overall correlated with borough and 2 other fieldsHigh correlation
borough is highly overall correlated with bbl and 6 other fieldsHigh correlation
incident_zip is highly overall correlated with bbl and 4 other fieldsHigh correlation
latitude is highly overall correlated with borough and 2 other fieldsHigh correlation
longitude is highly overall correlated with borough and 3 other fieldsHigh correlation
park_borough is highly overall correlated with bbl and 6 other fieldsHigh correlation
resolution_description is highly overall correlated with statusHigh correlation
status is highly overall correlated with resolution_description and 1 other fieldsHigh correlation
unique_key is highly overall correlated with statusHigh correlation
x_coordinate_state_plane is highly overall correlated with borough and 3 other fieldsHigh correlation
y_coordinate_state_plane is highly overall correlated with borough and 2 other fieldsHigh correlation
location_type is highly imbalanced (84.5%) Imbalance
address_type is highly imbalanced (90.8%) Imbalance
status is highly imbalanced (67.2%) Imbalance
park_facility_name is highly imbalanced (99.9%) Imbalance
resolution_description is highly imbalanced (87.0%) Imbalance
incident_zip has 1566 (2.7%) missing values Missing
incident_address has 1594 (2.7%) missing values Missing
street_name has 1700 (2.9%) missing values Missing
cross_street_1 has 2381 (4.0%) missing values Missing
cross_street_2 has 2375 (4.0%) missing values Missing
intersection_street_1 has 4075 (6.9%) missing values Missing
intersection_street_2 has 4068 (6.9%) missing values Missing
address_type has 1949 (3.3%) missing values Missing
city has 2100 (3.6%) missing values Missing
landmark has 7431 (12.6%) missing values Missing
bbl has 4054 (6.9%) missing values Missing
x_coordinate_state_plane has 1566 (2.7%) missing values Missing
y_coordinate_state_plane has 1564 (2.7%) missing values Missing
latitude has 1569 (2.7%) missing values Missing
longitude has 1569 (2.7%) missing values Missing
location has 1569 (2.7%) missing values Missing
closed_date has 6875 (11.7%) missing values Missing
resolution_description has 5769 (9.8%) missing values Missing
resolution_action_updated_date has 5769 (9.8%) missing values Missing
due_date has 53677 (91.1%) missing values Missing
facility_type has 58913 (100.0%) missing values Missing
unique_key has unique values Unique
facility_type is an unsupported type, check if it needs cleaning or further analysis Unsupported

Reproduction

Analysis started2024-11-19 05:02:10.371907
Analysis finished2024-11-19 05:45:56.688048
Duration43 minutes and 46.32 seconds
Software versionydata-profiling vv4.12.0
Download configurationconfig.json

Variables

unique_key
Real number (ℝ)

High correlation  Unique 

Distinct58913
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52693783
Minimum41307236
Maximum62607416
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size460.4 KiB
2024-11-19T00:47:19.048117image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum41307236
5-th percentile42235314
Q146443669
median53699381
Q358293912
95-th percentile61841452
Maximum62607416
Range21300180
Interquartile range (IQR)11850243

Descriptive statistics

Standard deviation6438895.9
Coefficient of variation (CV)0.1221946
Kurtosis-1.2598773
Mean52693783
Median Absolute Deviation (MAD)5638417
Skewness-0.20788897
Sum3.1043488 × 1012
Variance4.145938 × 1013
MonotonicityNot monotonic
2024-11-19T00:47:19.208645image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41307236 1
 
< 0.1%
41318285 1
 
< 0.1%
41316446 1
 
< 0.1%
41316887 1
 
< 0.1%
41318573 1
 
< 0.1%
41317956 1
 
< 0.1%
41315009 1
 
< 0.1%
41318163 1
 
< 0.1%
41319075 1
 
< 0.1%
41317825 1
 
< 0.1%
Other values (58903) 58903
> 99.9%
ValueCountFrequency (%)
41307236 1
< 0.1%
41314791 1
< 0.1%
41314982 1
< 0.1%
41315009 1
< 0.1%
41315010 1
< 0.1%
41315466 1
< 0.1%
41316420 1
< 0.1%
41316445 1
< 0.1%
41316446 1
< 0.1%
41316449 1
< 0.1%
ValueCountFrequency (%)
62607416 1
< 0.1%
62607315 1
< 0.1%
62606493 1
< 0.1%
62606492 1
< 0.1%
62606141 1
< 0.1%
62605637 1
< 0.1%
62605571 1
< 0.1%
62605500 1
< 0.1%
62604774 1
< 0.1%
62604570 1
< 0.1%
Distinct58896
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Memory size460.4 KiB
Minimum2019-01-01 01:17:04
Maximum2024-09-29 23:42:42
2024-11-19T00:47:19.374245image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:47:19.569726image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

agency
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size460.4 KiB
DOHMH
58913 

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters294565
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDOHMH
2nd rowDOHMH
3rd rowDOHMH
4th rowDOHMH
5th rowDOHMH

Common Values

ValueCountFrequency (%)
DOHMH 58913
100.0%

Length

2024-11-19T00:47:19.745214image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-19T00:47:19.872962image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
dohmh 58913
100.0%

Most occurring characters

ValueCountFrequency (%)
H 117826
40.0%
D 58913
20.0%
O 58913
20.0%
M 58913
20.0%

Most occurring categories

ValueCountFrequency (%)
(unknown) 294565
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
H 117826
40.0%
D 58913
20.0%
O 58913
20.0%
M 58913
20.0%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 294565
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
H 117826
40.0%
D 58913
20.0%
O 58913
20.0%
M 58913
20.0%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 294565
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
H 117826
40.0%
D 58913
20.0%
O 58913
20.0%
M 58913
20.0%

agency_name
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size460.4 KiB
Department of Health and Mental Hygiene
58913 

Length

Max length39
Median length39
Mean length39
Min length39

Characters and Unicode

Total characters2297607
Distinct characters19
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDepartment of Health and Mental Hygiene
2nd rowDepartment of Health and Mental Hygiene
3rd rowDepartment of Health and Mental Hygiene
4th rowDepartment of Health and Mental Hygiene
5th rowDepartment of Health and Mental Hygiene

Common Values

ValueCountFrequency (%)
Department of Health and Mental Hygiene 58913
100.0%

Length

2024-11-19T00:47:19.992641image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-19T00:47:20.105340image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
department 58913
16.7%
of 58913
16.7%
health 58913
16.7%
and 58913
16.7%
mental 58913
16.7%
hygiene 58913
16.7%

Most occurring characters

ValueCountFrequency (%)
e 353478
15.4%
294565
12.8%
a 235652
10.3%
n 235652
10.3%
t 235652
10.3%
l 117826
 
5.1%
H 117826
 
5.1%
p 58913
 
2.6%
D 58913
 
2.6%
m 58913
 
2.6%
Other values (9) 530217
23.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 2297607
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 353478
15.4%
294565
12.8%
a 235652
10.3%
n 235652
10.3%
t 235652
10.3%
l 117826
 
5.1%
H 117826
 
5.1%
p 58913
 
2.6%
D 58913
 
2.6%
m 58913
 
2.6%
Other values (9) 530217
23.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 2297607
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 353478
15.4%
294565
12.8%
a 235652
10.3%
n 235652
10.3%
t 235652
10.3%
l 117826
 
5.1%
H 117826
 
5.1%
p 58913
 
2.6%
D 58913
 
2.6%
m 58913
 
2.6%
Other values (9) 530217
23.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 2297607
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 353478
15.4%
294565
12.8%
a 235652
10.3%
n 235652
10.3%
t 235652
10.3%
l 117826
 
5.1%
H 117826
 
5.1%
p 58913
 
2.6%
D 58913
 
2.6%
m 58913
 
2.6%
Other values (9) 530217
23.1%

complaint_type
Categorical

Constant 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size460.4 KiB
Food Establishment
58913 

Length

Max length18
Median length18
Mean length18
Min length18

Characters and Unicode

Total characters1060434
Distinct characters15
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFood Establishment
2nd rowFood Establishment
3rd rowFood Establishment
4th rowFood Establishment
5th rowFood Establishment

Common Values

ValueCountFrequency (%)
Food Establishment 58913
100.0%

Length

2024-11-19T00:47:20.225331image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-19T00:47:20.338030image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
food 58913
50.0%
establishment 58913
50.0%

Most occurring characters

ValueCountFrequency (%)
o 117826
 
11.1%
s 117826
 
11.1%
t 117826
 
11.1%
d 58913
 
5.6%
F 58913
 
5.6%
E 58913
 
5.6%
58913
 
5.6%
a 58913
 
5.6%
b 58913
 
5.6%
l 58913
 
5.6%
Other values (5) 294565
27.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1060434
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
o 117826
 
11.1%
s 117826
 
11.1%
t 117826
 
11.1%
d 58913
 
5.6%
F 58913
 
5.6%
E 58913
 
5.6%
58913
 
5.6%
a 58913
 
5.6%
b 58913
 
5.6%
l 58913
 
5.6%
Other values (5) 294565
27.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1060434
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
o 117826
 
11.1%
s 117826
 
11.1%
t 117826
 
11.1%
d 58913
 
5.6%
F 58913
 
5.6%
E 58913
 
5.6%
58913
 
5.6%
a 58913
 
5.6%
b 58913
 
5.6%
l 58913
 
5.6%
Other values (5) 294565
27.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1060434
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
o 117826
 
11.1%
s 117826
 
11.1%
t 117826
 
11.1%
d 58913
 
5.6%
F 58913
 
5.6%
E 58913
 
5.6%
58913
 
5.6%
a 58913
 
5.6%
b 58913
 
5.6%
l 58913
 
5.6%
Other values (5) 294565
27.8%

descriptor
Categorical

Distinct32
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size460.4 KiB
Rodents/Insects/Garbage
19324 
Food Spoiled
4723 
Bare Hands in Contact w/ Food
4699 
Food Contaminated
3976 
Letter Grading
3504 
Other values (27)
22687 

Length

Max length29
Median length25
Mean length19.491521
Min length4

Characters and Unicode

Total characters1148304
Distinct characters47
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBare Hands in Contact w/ Food
2nd rowRodents/Insects/Garbage
3rd rowRodents/Insects/Garbage
4th rowRodents/Insects/Garbage
5th rowBare Hands in Contact w/ Food

Common Values

ValueCountFrequency (%)
Rodents/Insects/Garbage 19324
32.8%
Food Spoiled 4723
 
8.0%
Bare Hands in Contact w/ Food 4699
 
8.0%
Food Contaminated 3976
 
6.7%
Letter Grading 3504
 
5.9%
No Permit or License 2843
 
4.8%
Pet/Animal 2683
 
4.6%
Food Worker Hygiene 2434
 
4.1%
Food Contains Foreign Object 2278
 
3.9%
Kitchen/Food Prep Area 1963
 
3.3%
Other values (22) 10486
17.8%

Length

2024-11-19T00:47:20.474665image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
food 22225
17.5%
rodents/insects/garbage 19324
 
15.2%
spoiled 4723
 
3.7%
bare 4699
 
3.7%
hands 4699
 
3.7%
in 4699
 
3.7%
contact 4699
 
3.7%
w 4699
 
3.7%
contaminated 3976
 
3.1%
letter 3504
 
2.8%
Other values (43) 49535
39.1%

Most occurring characters

ValueCountFrequency (%)
e 120934
 
10.5%
o 104044
 
9.1%
t 89063
 
7.8%
n 88461
 
7.7%
a 80050
 
7.0%
s 71805
 
6.3%
67869
 
5.9%
d 62604
 
5.5%
r 58592
 
5.1%
/ 49676
 
4.3%
Other values (37) 355206
30.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1148304
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 120934
 
10.5%
o 104044
 
9.1%
t 89063
 
7.8%
n 88461
 
7.7%
a 80050
 
7.0%
s 71805
 
6.3%
67869
 
5.9%
d 62604
 
5.5%
r 58592
 
5.1%
/ 49676
 
4.3%
Other values (37) 355206
30.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1148304
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 120934
 
10.5%
o 104044
 
9.1%
t 89063
 
7.8%
n 88461
 
7.7%
a 80050
 
7.0%
s 71805
 
6.3%
67869
 
5.9%
d 62604
 
5.5%
r 58592
 
5.1%
/ 49676
 
4.3%
Other values (37) 355206
30.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1148304
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 120934
 
10.5%
o 104044
 
9.1%
t 89063
 
7.8%
n 88461
 
7.7%
a 80050
 
7.0%
s 71805
 
6.3%
67869
 
5.9%
d 62604
 
5.5%
r 58592
 
5.1%
/ 49676
 
4.3%
Other values (37) 355206
30.9%

location_type
Categorical

Imbalance 

Distinct40
Distinct (%)0.1%
Missing14
Missing (%)< 0.1%
Memory size460.4 KiB
Restaurant/Bar/Deli/Bakery
52088 
Other (Explain Below)
 
3654
1-2 Family Dwelling
 
759
Restaurant
 
713
Catering Service
 
266
Other values (35)
 
1419

Length

Max length36
Median length26
Mean length25.182074
Min length5

Characters and Unicode

Total characters1483199
Distinct characters50
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)< 0.1%

Sample

1st rowRestaurant/Bar/Deli/Bakery
2nd rowRestaurant/Bar/Deli/Bakery
3rd rowRestaurant/Bar/Deli/Bakery
4th rowRestaurant/Bar/Deli/Bakery
5th rowRestaurant/Bar/Deli/Bakery

Common Values

ValueCountFrequency (%)
Restaurant/Bar/Deli/Bakery 52088
88.4%
Other (Explain Below) 3654
 
6.2%
1-2 Family Dwelling 759
 
1.3%
Restaurant 713
 
1.2%
Catering Service 266
 
0.5%
Other (explain in Complaint Details) 210
 
0.4%
Commercial Building 153
 
0.3%
Store 145
 
0.2%
Residence 142
 
0.2%
Cafeteria - College/University 101
 
0.2%
Other values (30) 668
 
1.1%

Length

2024-11-19T00:47:20.642796image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
restaurant/bar/deli/bakery 52088
74.1%
other 3954
 
5.6%
explain 3864
 
5.5%
below 3654
 
5.2%
family 832
 
1.2%
1-2 808
 
1.2%
dwelling 759
 
1.1%
restaurant 713
 
1.0%
catering 278
 
0.4%
service 266
 
0.4%
Other values (48) 3034
 
4.3%

Most occurring characters

ValueCountFrequency (%)
a 216044
14.6%
e 169034
11.4%
r 162803
11.0%
/ 156366
10.5%
t 111321
 
7.5%
B 108076
 
7.3%
l 63155
 
4.3%
i 60359
 
4.1%
n 59058
 
4.0%
s 53339
 
3.6%
Other values (40) 323644
21.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1483199
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a 216044
14.6%
e 169034
11.4%
r 162803
11.0%
/ 156366
10.5%
t 111321
 
7.5%
B 108076
 
7.3%
l 63155
 
4.3%
i 60359
 
4.1%
n 59058
 
4.0%
s 53339
 
3.6%
Other values (40) 323644
21.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1483199
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a 216044
14.6%
e 169034
11.4%
r 162803
11.0%
/ 156366
10.5%
t 111321
 
7.5%
B 108076
 
7.3%
l 63155
 
4.3%
i 60359
 
4.1%
n 59058
 
4.0%
s 53339
 
3.6%
Other values (40) 323644
21.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1483199
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a 216044
14.6%
e 169034
11.4%
r 162803
11.0%
/ 156366
10.5%
t 111321
 
7.5%
B 108076
 
7.3%
l 63155
 
4.3%
i 60359
 
4.1%
n 59058
 
4.0%
s 53339
 
3.6%
Other values (40) 323644
21.8%

incident_zip
Real number (ℝ)

High correlation  Missing 

Distinct211
Distinct (%)0.4%
Missing1566
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean10725.561
Minimum10000
Maximum12345
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size460.4 KiB
2024-11-19T00:47:20.803368image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum10000
5-th percentile10004
Q110028
median11103
Q311232
95-th percentile11419
Maximum12345
Range2345
Interquartile range (IQR)1204

Descriptive statistics

Standard deviation587.41274
Coefficient of variation (CV)0.054767555
Kurtosis-1.78548
Mean10725.561
Median Absolute Deviation (MAD)331
Skewness-0.13598334
Sum6.1507873 × 108
Variance345053.73
MonotonicityNot monotonic
2024-11-19T00:47:20.976902image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10003 1175
 
2.0%
11355 1102
 
1.9%
11201 1048
 
1.8%
10019 1021
 
1.7%
10002 940
 
1.6%
10014 871
 
1.5%
10013 833
 
1.4%
10036 817
 
1.4%
11209 800
 
1.4%
10011 792
 
1.3%
Other values (201) 47948
81.4%
(Missing) 1566
 
2.7%
ValueCountFrequency (%)
10000 6
 
< 0.1%
10001 738
1.3%
10002 940
1.6%
10003 1175
2.0%
10004 131
 
0.2%
10005 84
 
0.1%
10006 48
 
0.1%
10007 258
 
0.4%
10009 679
1.2%
10010 430
 
0.7%
ValueCountFrequency (%)
12345 1
 
< 0.1%
11697 6
 
< 0.1%
11695 3
 
< 0.1%
11694 104
0.2%
11693 84
 
0.1%
11692 34
 
0.1%
11691 123
0.2%
11436 74
 
0.1%
11435 252
0.4%
11434 257
0.4%

incident_address
Text

Missing 

Distinct25182
Distinct (%)43.9%
Missing1594
Missing (%)2.7%
Memory size460.4 KiB
2024-11-19T00:47:21.544534image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length38
Median length33
Mean length18.08095
Min length1

Characters and Unicode

Total characters1036382
Distinct characters40
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14513 ?
Unique (%)25.3%

Sample

1st row523 BRIGHTON BEACH AVENUE
2nd row2117 WILLIAMBRIDGE ROAD
3rd row31 WEST 32 STREET
4th row114
5th row2605 CONEY ISLAND AVENUE
ValueCountFrequency (%)
avenue 26908
 
14.8%
street 17513
 
9.7%
boulevard 5281
 
2.9%
east 4002
 
2.2%
west 3669
 
2.0%
broadway 2497
 
1.4%
road 1907
 
1.1%
3 1295
 
0.7%
5 998
 
0.6%
1 976
 
0.5%
Other values (9424) 116197
64.1%
2024-11-19T00:47:22.259845image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
134720
 
13.0%
E 127894
 
12.3%
A 68491
 
6.6%
T 62822
 
6.1%
N 51377
 
5.0%
R 50832
 
4.9%
1 44804
 
4.3%
S 42663
 
4.1%
U 40865
 
3.9%
V 34982
 
3.4%
Other values (30) 376932
36.4%

Most occurring categories

ValueCountFrequency (%)
(unknown) 1036382
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
134720
 
13.0%
E 127894
 
12.3%
A 68491
 
6.6%
T 62822
 
6.1%
N 51377
 
5.0%
R 50832
 
4.9%
1 44804
 
4.3%
S 42663
 
4.1%
U 40865
 
3.9%
V 34982
 
3.4%
Other values (30) 376932
36.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 1036382
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
134720
 
13.0%
E 127894
 
12.3%
A 68491
 
6.6%
T 62822
 
6.1%
N 51377
 
5.0%
R 50832
 
4.9%
1 44804
 
4.3%
S 42663
 
4.1%
U 40865
 
3.9%
V 34982
 
3.4%
Other values (30) 376932
36.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 1036382
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
134720
 
13.0%
E 127894
 
12.3%
A 68491
 
6.6%
T 62822
 
6.1%
N 51377
 
5.0%
R 50832
 
4.9%
1 44804
 
4.3%
S 42663
 
4.1%
U 40865
 
3.9%
V 34982
 
3.4%
Other values (30) 376932
36.4%

street_name
Text

Missing 

Distinct2574
Distinct (%)4.5%
Missing1700
Missing (%)2.9%
Memory size460.4 KiB
2024-11-19T00:47:22.714081image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length32
Median length29
Mean length13.479506
Min length3

Characters and Unicode

Total characters771203
Distinct characters39
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique728 ?
Unique (%)1.3%

Sample

1st rowBRIGHTON BEACH AVENUE
2nd rowWILLIAMBRIDGE ROAD
3rd rowWEST 32 STREET
4th rowCONEY ISLAND AVENUE
5th rowPROSPECT PARK WEST
ValueCountFrequency (%)
avenue 26908
21.6%
street 17513
 
14.0%
boulevard 5281
 
4.2%
east 3997
 
3.2%
west 3661
 
2.9%
broadway 2497
 
2.0%
road 1907
 
1.5%
3 1261
 
1.0%
5 898
 
0.7%
8 884
 
0.7%
Other values (1524) 59885
48.0%
2024-11-19T00:47:23.335288image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 127862
16.6%
78275
10.1%
A 68213
 
8.8%
T 62807
 
8.1%
N 51373
 
6.7%
R 50830
 
6.6%
S 42637
 
5.5%
U 40865
 
5.3%
V 34982
 
4.5%
O 29965
 
3.9%
Other values (29) 183394
23.8%

Most occurring categories

ValueCountFrequency (%)
(unknown) 771203
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 127862
16.6%
78275
10.1%
A 68213
 
8.8%
T 62807
 
8.1%
N 51373
 
6.7%
R 50830
 
6.6%
S 42637
 
5.5%
U 40865
 
5.3%
V 34982
 
4.5%
O 29965
 
3.9%
Other values (29) 183394
23.8%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 771203
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 127862
16.6%
78275
10.1%
A 68213
 
8.8%
T 62807
 
8.1%
N 51373
 
6.7%
R 50830
 
6.6%
S 42637
 
5.5%
U 40865
 
5.3%
V 34982
 
4.5%
O 29965
 
3.9%
Other values (29) 183394
23.8%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 771203
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 127862
16.6%
78275
10.1%
A 68213
 
8.8%
T 62807
 
8.1%
N 51373
 
6.7%
R 50830
 
6.6%
S 42637
 
5.5%
U 40865
 
5.3%
V 34982
 
4.5%
O 29965
 
3.9%
Other values (29) 183394
23.8%

cross_street_1
Text

Missing 

Distinct4021
Distinct (%)7.1%
Missing2381
Missing (%)4.0%
Memory size460.4 KiB
2024-11-19T00:47:23.853945image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length32
Median length29
Mean length13.350403
Min length4

Characters and Unicode

Total characters754725
Distinct characters43
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique887 ?
Unique (%)1.6%

Sample

1st rowBRIGHTON 5 STREET
2nd rowLYDIG AVENUE
3rd row5 AVENUE
4th rowBERRY STRE
5th rowAVENUE W
ValueCountFrequency (%)
street 28877
21.9%
avenue 18298
 
13.9%
east 6567
 
5.0%
west 5623
 
4.3%
place 2009
 
1.5%
road 1591
 
1.2%
boulevard 1242
 
0.9%
5 1158
 
0.9%
barclay 711
 
0.5%
broadway 700
 
0.5%
Other values (2541) 65057
49.3%
2024-11-19T00:47:24.547089image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 134512
17.8%
96128
12.7%
T 83274
11.0%
A 53813
 
7.1%
R 53664
 
7.1%
S 53312
 
7.1%
N 37705
 
5.0%
U 24960
 
3.3%
V 21926
 
2.9%
O 20077
 
2.7%
Other values (33) 175354
23.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 754725
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 134512
17.8%
96128
12.7%
T 83274
11.0%
A 53813
 
7.1%
R 53664
 
7.1%
S 53312
 
7.1%
N 37705
 
5.0%
U 24960
 
3.3%
V 21926
 
2.9%
O 20077
 
2.7%
Other values (33) 175354
23.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 754725
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 134512
17.8%
96128
12.7%
T 83274
11.0%
A 53813
 
7.1%
R 53664
 
7.1%
S 53312
 
7.1%
N 37705
 
5.0%
U 24960
 
3.3%
V 21926
 
2.9%
O 20077
 
2.7%
Other values (33) 175354
23.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 754725
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 134512
17.8%
96128
12.7%
T 83274
11.0%
A 53813
 
7.1%
R 53664
 
7.1%
S 53312
 
7.1%
N 37705
 
5.0%
U 24960
 
3.3%
V 21926
 
2.9%
O 20077
 
2.7%
Other values (33) 175354
23.2%

cross_street_2
Text

Missing 

Distinct4049
Distinct (%)7.2%
Missing2375
Missing (%)4.0%
Memory size460.4 KiB
2024-11-19T00:47:25.064665image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length32
Median length29
Mean length13.42559
Min length4

Characters and Unicode

Total characters759056
Distinct characters43
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique910 ?
Unique (%)1.6%

Sample

1st rowBRIGHTON 6 STREET
2nd rowPELHAM PARKWAY SOUTH
3rd rowBROADWAY
4th rowMIKE LEE
5th rowLANCASTER AVENUE
ValueCountFrequency (%)
street 28887
21.8%
avenue 17975
 
13.6%
east 6567
 
5.0%
west 5907
 
4.5%
place 2072
 
1.6%
road 1896
 
1.4%
boulevard 1177
 
0.9%
broadway 746
 
0.6%
sanford 736
 
0.6%
3 681
 
0.5%
Other values (2525) 65600
49.6%
2024-11-19T00:47:25.883187image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 133901
17.6%
96979
12.8%
T 84232
11.1%
S 54579
 
7.2%
R 53668
 
7.1%
A 52734
 
6.9%
N 39705
 
5.2%
U 24730
 
3.3%
O 22668
 
3.0%
V 21776
 
2.9%
Other values (33) 174084
22.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 759056
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 133901
17.6%
96979
12.8%
T 84232
11.1%
S 54579
 
7.2%
R 53668
 
7.1%
A 52734
 
6.9%
N 39705
 
5.2%
U 24730
 
3.3%
O 22668
 
3.0%
V 21776
 
2.9%
Other values (33) 174084
22.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 759056
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 133901
17.6%
96979
12.8%
T 84232
11.1%
S 54579
 
7.2%
R 53668
 
7.1%
A 52734
 
6.9%
N 39705
 
5.2%
U 24730
 
3.3%
O 22668
 
3.0%
V 21776
 
2.9%
Other values (33) 174084
22.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 759056
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 133901
17.6%
96979
12.8%
T 84232
11.1%
S 54579
 
7.2%
R 53668
 
7.1%
A 52734
 
6.9%
N 39705
 
5.2%
U 24730
 
3.3%
O 22668
 
3.0%
V 21776
 
2.9%
Other values (33) 174084
22.9%

intersection_street_1
Text

Missing 

Distinct3929
Distinct (%)7.2%
Missing4075
Missing (%)6.9%
Memory size460.4 KiB
2024-11-19T00:47:26.398849image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length32
Median length29
Mean length13.372625
Min length4

Characters and Unicode

Total characters733328
Distinct characters43
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique894 ?
Unique (%)1.6%

Sample

1st rowBRIGHTON 5 STREET
2nd rowLYDIG AVENUE
3rd row5 AVENUE
4th rowBERRY STRE
5th rowAVENUE W
ValueCountFrequency (%)
street 27986
21.9%
avenue 17785
 
13.9%
east 6352
 
5.0%
west 5414
 
4.2%
place 1949
 
1.5%
road 1522
 
1.2%
boulevard 1214
 
0.9%
5 1107
 
0.9%
barclay 711
 
0.6%
broadway 680
 
0.5%
Other values (2535) 63168
49.4%
2024-11-19T00:47:27.091999image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 130535
17.8%
93911
12.8%
T 80684
11.0%
A 52269
 
7.1%
R 52125
 
7.1%
S 51662
 
7.0%
N 36693
 
5.0%
U 24257
 
3.3%
V 21341
 
2.9%
O 19518
 
2.7%
Other values (33) 170333
23.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 733328
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 130535
17.8%
93911
12.8%
T 80684
11.0%
A 52269
 
7.1%
R 52125
 
7.1%
S 51662
 
7.0%
N 36693
 
5.0%
U 24257
 
3.3%
V 21341
 
2.9%
O 19518
 
2.7%
Other values (33) 170333
23.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 733328
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 130535
17.8%
93911
12.8%
T 80684
11.0%
A 52269
 
7.1%
R 52125
 
7.1%
S 51662
 
7.0%
N 36693
 
5.0%
U 24257
 
3.3%
V 21341
 
2.9%
O 19518
 
2.7%
Other values (33) 170333
23.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 733328
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 130535
17.8%
93911
12.8%
T 80684
11.0%
A 52269
 
7.1%
R 52125
 
7.1%
S 51662
 
7.0%
N 36693
 
5.0%
U 24257
 
3.3%
V 21341
 
2.9%
O 19518
 
2.7%
Other values (33) 170333
23.2%

intersection_street_2
Text

Missing 

Distinct3949
Distinct (%)7.2%
Missing4068
Missing (%)6.9%
Memory size460.4 KiB
2024-11-19T00:47:27.610567image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length32
Median length29
Mean length13.447698
Min length4

Characters and Unicode

Total characters737539
Distinct characters43
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique915 ?
Unique (%)1.7%

Sample

1st rowBRIGHTON 6 STREET
2nd rowPELHAM PARKWAY SOUTH
3rd rowBROADWAY
4th rowMIKE LEE
5th rowLANCASTER AVENUE
ValueCountFrequency (%)
street 27982
21.8%
avenue 17471
 
13.6%
east 6350
 
5.0%
west 5696
 
4.4%
place 2008
 
1.6%
road 1833
 
1.4%
boulevard 1149
 
0.9%
sanford 734
 
0.6%
broadway 723
 
0.6%
3 647
 
0.5%
Other values (2513) 63679
49.6%
2024-11-19T00:47:28.322216image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 129948
17.6%
94721
12.8%
T 81605
11.1%
S 52921
 
7.2%
R 52178
 
7.1%
A 51241
 
6.9%
N 38679
 
5.2%
U 24047
 
3.3%
O 22091
 
3.0%
V 21172
 
2.9%
Other values (33) 168936
22.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 737539
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 129948
17.6%
94721
12.8%
T 81605
11.1%
S 52921
 
7.2%
R 52178
 
7.1%
A 51241
 
6.9%
N 38679
 
5.2%
U 24047
 
3.3%
O 22091
 
3.0%
V 21172
 
2.9%
Other values (33) 168936
22.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 737539
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 129948
17.6%
94721
12.8%
T 81605
11.1%
S 52921
 
7.2%
R 52178
 
7.1%
A 51241
 
6.9%
N 38679
 
5.2%
U 24047
 
3.3%
O 22091
 
3.0%
V 21172
 
2.9%
Other values (33) 168936
22.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 737539
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 129948
17.6%
94721
12.8%
T 81605
11.1%
S 52921
 
7.2%
R 52178
 
7.1%
A 51241
 
6.9%
N 38679
 
5.2%
U 24047
 
3.3%
O 22091
 
3.0%
V 21172
 
2.9%
Other values (33) 168936
22.9%

address_type
Categorical

Imbalance  Missing 

Distinct6
Distinct (%)< 0.1%
Missing1949
Missing (%)3.3%
Memory size460.4 KiB
ADDRESS
55263 
LATLONG
 
805
INTERSECTION
 
735
UNRECOGNIZED
 
123
BLOCKFACE
 
35

Length

Max length12
Median length7
Mean length7.0766449
Min length7

Characters and Unicode

Total characters403114
Distinct characters19
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowADDRESS
2nd rowADDRESS
3rd rowADDRESS
4th rowADDRESS
5th rowADDRESS

Common Values

ValueCountFrequency (%)
ADDRESS 55263
93.8%
LATLONG 805
 
1.4%
INTERSECTION 735
 
1.2%
UNRECOGNIZED 123
 
0.2%
BLOCKFACE 35
 
0.1%
PLACENAME 3
 
< 0.1%
(Missing) 1949
 
3.3%

Length

2024-11-19T00:47:28.486774image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-19T00:47:28.621413image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
address 55263
97.0%
latlong 805
 
1.4%
intersection 735
 
1.3%
unrecognized 123
 
0.2%
blockface 35
 
0.1%
placename 3
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
S 111261
27.6%
D 110649
27.4%
E 57020
14.1%
R 56121
13.9%
A 56109
13.9%
N 2524
 
0.6%
T 2275
 
0.6%
O 1698
 
0.4%
L 1648
 
0.4%
I 1593
 
0.4%
Other values (9) 2216
 
0.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 403114
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
S 111261
27.6%
D 110649
27.4%
E 57020
14.1%
R 56121
13.9%
A 56109
13.9%
N 2524
 
0.6%
T 2275
 
0.6%
O 1698
 
0.4%
L 1648
 
0.4%
I 1593
 
0.4%
Other values (9) 2216
 
0.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 403114
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
S 111261
27.6%
D 110649
27.4%
E 57020
14.1%
R 56121
13.9%
A 56109
13.9%
N 2524
 
0.6%
T 2275
 
0.6%
O 1698
 
0.4%
L 1648
 
0.4%
I 1593
 
0.4%
Other values (9) 2216
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 403114
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
S 111261
27.6%
D 110649
27.4%
E 57020
14.1%
R 56121
13.9%
A 56109
13.9%
N 2524
 
0.6%
T 2275
 
0.6%
O 1698
 
0.4%
L 1648
 
0.4%
I 1593
 
0.4%
Other values (9) 2216
 
0.5%

city
Text

Missing 

Distinct56
Distinct (%)0.1%
Missing2100
Missing (%)3.6%
Memory size460.4 KiB
2024-11-19T00:47:28.919653image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length19
Median length8
Mean length8.4094485
Min length2

Characters and Unicode

Total characters477766
Distinct characters48
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)< 0.1%

Sample

1st rowBROOKLYN
2nd rowBRONX
3rd rowNEW YORK
4th rowBrooklyn
5th rowBROOKLYN
ValueCountFrequency (%)
new 19424
22.8%
york 19410
22.7%
brooklyn 15888
18.6%
bronx 5705
 
6.7%
island 2938
 
3.4%
staten 2377
 
2.8%
flushing 2211
 
2.6%
astoria 1591
 
1.9%
jamaica 1246
 
1.5%
park 823
 
1.0%
Other values (52) 13712
16.1%
2024-11-19T00:47:29.374946image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
O 67492
14.1%
N 53053
11.1%
R 48319
10.1%
K 37347
 
7.8%
Y 36611
 
7.7%
E 29866
 
6.3%
28512
 
6.0%
L 26898
 
5.6%
B 22255
 
4.7%
W 21490
 
4.5%
Other values (38) 105923
22.2%

Most occurring categories

ValueCountFrequency (%)
(unknown) 477766
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
O 67492
14.1%
N 53053
11.1%
R 48319
10.1%
K 37347
 
7.8%
Y 36611
 
7.7%
E 29866
 
6.3%
28512
 
6.0%
L 26898
 
5.6%
B 22255
 
4.7%
W 21490
 
4.5%
Other values (38) 105923
22.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 477766
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
O 67492
14.1%
N 53053
11.1%
R 48319
10.1%
K 37347
 
7.8%
Y 36611
 
7.7%
E 29866
 
6.3%
28512
 
6.0%
L 26898
 
5.6%
B 22255
 
4.7%
W 21490
 
4.5%
Other values (38) 105923
22.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 477766
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
O 67492
14.1%
N 53053
11.1%
R 48319
10.1%
K 37347
 
7.8%
Y 36611
 
7.7%
E 29866
 
6.3%
28512
 
6.0%
L 26898
 
5.6%
B 22255
 
4.7%
W 21490
 
4.5%
Other values (38) 105923
22.2%

landmark
Text

Missing 

Distinct2080
Distinct (%)4.0%
Missing7431
Missing (%)12.6%
Memory size460.4 KiB
2024-11-19T00:47:29.830682image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length32
Median length29
Mean length13.424556
Min length6

Characters and Unicode

Total characters691123
Distinct characters38
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique537 ?
Unique (%)1.0%

Sample

1st rowBRIGHTON BEACH AVENUE
2nd rowWILLIAMSBRIDGE ROAD
3rd rowWEST 32 STREET
4th rowCONEY ISLAND AVENUE
5th rowPROSPECT PARK WEST
ValueCountFrequency (%)
avenue 24476
21.8%
street 15759
 
14.0%
boulevard 4514
 
4.0%
east 3572
 
3.2%
west 3272
 
2.9%
broadway 2203
 
2.0%
road 1744
 
1.6%
3 1267
 
1.1%
8 962
 
0.9%
5 891
 
0.8%
Other values (1359) 53752
47.8%
2024-11-19T00:47:30.458807image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
E 115202
16.7%
71719
10.4%
A 61195
 
8.9%
T 56125
 
8.1%
N 46278
 
6.7%
R 45270
 
6.6%
S 38258
 
5.5%
U 36657
 
5.3%
V 31459
 
4.6%
O 26530
 
3.8%
Other values (28) 162430
23.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 691123
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
E 115202
16.7%
71719
10.4%
A 61195
 
8.9%
T 56125
 
8.1%
N 46278
 
6.7%
R 45270
 
6.6%
S 38258
 
5.5%
U 36657
 
5.3%
V 31459
 
4.6%
O 26530
 
3.8%
Other values (28) 162430
23.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 691123
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
E 115202
16.7%
71719
10.4%
A 61195
 
8.9%
T 56125
 
8.1%
N 46278
 
6.7%
R 45270
 
6.6%
S 38258
 
5.5%
U 36657
 
5.3%
V 31459
 
4.6%
O 26530
 
3.8%
Other values (28) 162430
23.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 691123
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
E 115202
16.7%
71719
10.4%
A 61195
 
8.9%
T 56125
 
8.1%
N 46278
 
6.7%
R 45270
 
6.6%
S 38258
 
5.5%
U 36657
 
5.3%
V 31459
 
4.6%
O 26530
 
3.8%
Other values (28) 162430
23.5%

status
Categorical

High correlation  Imbalance 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size460.4 KiB
Closed
52034 
In Progress
6876 
Unspecified
 
3

Length

Max length11
Median length6
Mean length6.583827
Min length6

Characters and Unicode

Total characters387873
Distinct characters17
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowIn Progress
2nd rowIn Progress
3rd rowIn Progress
4th rowIn Progress
5th rowIn Progress

Common Values

ValueCountFrequency (%)
Closed 52034
88.3%
In Progress 6876
 
11.7%
Unspecified 3
 
< 0.1%

Length

2024-11-19T00:47:30.625470image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-19T00:47:30.752134image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
closed 52034
79.1%
in 6876
 
10.5%
progress 6876
 
10.5%
unspecified 3
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
s 65789
17.0%
e 58916
15.2%
o 58910
15.2%
d 52037
13.4%
C 52034
13.4%
l 52034
13.4%
r 13752
 
3.5%
n 6879
 
1.8%
I 6876
 
1.8%
6876
 
1.8%
Other values (7) 13770
 
3.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 387873
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s 65789
17.0%
e 58916
15.2%
o 58910
15.2%
d 52037
13.4%
C 52034
13.4%
l 52034
13.4%
r 13752
 
3.5%
n 6879
 
1.8%
I 6876
 
1.8%
6876
 
1.8%
Other values (7) 13770
 
3.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 387873
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s 65789
17.0%
e 58916
15.2%
o 58910
15.2%
d 52037
13.4%
C 52034
13.4%
l 52034
13.4%
r 13752
 
3.5%
n 6879
 
1.8%
I 6876
 
1.8%
6876
 
1.8%
Other values (7) 13770
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 387873
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s 65789
17.0%
e 58916
15.2%
o 58910
15.2%
d 52037
13.4%
C 52034
13.4%
l 52034
13.4%
r 13752
 
3.5%
n 6879
 
1.8%
I 6876
 
1.8%
6876
 
1.8%
Other values (7) 13770
 
3.6%
Distinct76
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size460.4 KiB
2024-11-19T00:47:30.960616image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length25
Median length21
Mean length10.853479
Min length8

Characters and Unicode

Total characters639411
Distinct characters37
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row13 BROOKLYN
2nd row11 BRONX
3rd row05 MANHATTAN
4th rowUnspecified BROOKLYN
5th row15 BROOKLYN
ValueCountFrequency (%)
manhattan 19634
16.3%
brooklyn 16056
13.4%
queens 13576
11.3%
01 7043
 
5.9%
02 5849
 
4.9%
bronx 5782
 
4.8%
07 5535
 
4.6%
03 5212
 
4.3%
05 5012
 
4.2%
04 4048
 
3.4%
Other values (27) 32481
27.0%
2024-11-19T00:47:31.345588image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
N 79486
 
12.4%
A 63706
 
10.0%
61315
 
9.6%
0 48035
 
7.5%
T 44072
 
6.9%
O 37894
 
5.9%
E 29554
 
4.6%
1 24060
 
3.8%
B 21838
 
3.4%
R 21838
 
3.4%
Other values (27) 207613
32.5%

Most occurring categories

ValueCountFrequency (%)
(unknown) 639411
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N 79486
 
12.4%
A 63706
 
10.0%
61315
 
9.6%
0 48035
 
7.5%
T 44072
 
6.9%
O 37894
 
5.9%
E 29554
 
4.6%
1 24060
 
3.8%
B 21838
 
3.4%
R 21838
 
3.4%
Other values (27) 207613
32.5%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 639411
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N 79486
 
12.4%
A 63706
 
10.0%
61315
 
9.6%
0 48035
 
7.5%
T 44072
 
6.9%
O 37894
 
5.9%
E 29554
 
4.6%
1 24060
 
3.8%
B 21838
 
3.4%
R 21838
 
3.4%
Other values (27) 207613
32.5%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 639411
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N 79486
 
12.4%
A 63706
 
10.0%
61315
 
9.6%
0 48035
 
7.5%
T 44072
 
6.9%
O 37894
 
5.9%
E 29554
 
4.6%
1 24060
 
3.8%
B 21838
 
3.4%
R 21838
 
3.4%
Other values (27) 207613
32.5%

bbl
Real number (ℝ)

High correlation  Missing 

Distinct19057
Distinct (%)34.7%
Missing4054
Missing (%)6.9%
Infinite0
Infinite (%)0.0%
Mean2.5644265 × 109
Minimum0
Maximum5.2700005 × 109
Zeros2
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size460.4 KiB
2024-11-19T00:47:31.506117image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.00414 × 109
Q11.01443 × 109
median3.0115 × 109
Q34.00659 × 109
95-th percentile4.1404801 × 109
Maximum5.2700005 × 109
Range5.2700005 × 109
Interquartile range (IQR)2.99216 × 109

Descriptive statistics

Standard deviation1.3009651 × 109
Coefficient of variation (CV)0.50731231
Kurtosis-1.3553835
Mean2.5644265 × 109
Median Absolute Deviation (MAD)1.0382601 × 109
Skewness0.057951962
Sum1.4068187 × 1014
Variance1.6925102 × 1018
MonotonicityNot monotonic
2024-11-19T00:47:31.689627image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4050590011 693
 
1.2%
5007350081 411
 
0.7%
1015640024 146
 
0.2%
4032340173 91
 
0.2%
3027790001 88
 
0.1%
3033930049 85
 
0.1%
1018770031 76
 
0.1%
1000917502 72
 
0.1%
1010737505 69
 
0.1%
3039300028 64
 
0.1%
Other values (19047) 53064
90.1%
(Missing) 4054
 
6.9%
ValueCountFrequency (%)
0 2
 
< 0.1%
1000010111 1
 
< 0.1%
1000020001 6
< 0.1%
1000020002 3
< 0.1%
1000030001 3
< 0.1%
1000047501 1
 
< 0.1%
1000070027 1
 
< 0.1%
1000070028 3
< 0.1%
1000070031 7
< 0.1%
1000070035 7
< 0.1%
ValueCountFrequency (%)
5270000501 2
< 0.1%
5240009996 1
< 0.1%
5200479999 1
< 0.1%
5080470031 1
< 0.1%
5080470021 1
< 0.1%
5080430019 2
< 0.1%
5080430001 2
< 0.1%
5080340100 1
< 0.1%
5080260016 2
< 0.1%
5080260008 1
< 0.1%

borough
Categorical

High correlation 

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size460.4 KiB
MANHATTAN
19639 
BROOKLYN
16056 
QUEENS
13575 
BRONX
5778 
STATEN ISLAND
2402 

Length

Max length13
Median length11
Mean length7.8566361
Min length5

Characters and Unicode

Total characters462858
Distinct characters27
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBROOKLYN
2nd rowBRONX
3rd rowMANHATTAN
4th rowBROOKLYN
5th rowBROOKLYN

Common Values

ValueCountFrequency (%)
MANHATTAN 19639
33.3%
BROOKLYN 16056
27.3%
QUEENS 13575
23.0%
BRONX 5778
 
9.8%
STATEN ISLAND 2402
 
4.1%
Unspecified 1463
 
2.5%

Length

2024-11-19T00:47:31.859781image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-19T00:47:32.007384image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
manhattan 19639
32.0%
brooklyn 16056
26.2%
queens 13575
22.1%
bronx 5778
 
9.4%
staten 2402
 
3.9%
island 2402
 
3.9%
unspecified 1463
 
2.4%

Most occurring characters

ValueCountFrequency (%)
N 79491
17.2%
A 63721
13.8%
T 44082
9.5%
O 37890
 
8.2%
E 29552
 
6.4%
B 21834
 
4.7%
R 21834
 
4.7%
H 19639
 
4.2%
M 19639
 
4.2%
L 18458
 
4.0%
Other values (17) 106718
23.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 462858
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N 79491
17.2%
A 63721
13.8%
T 44082
9.5%
O 37890
 
8.2%
E 29552
 
6.4%
B 21834
 
4.7%
R 21834
 
4.7%
H 19639
 
4.2%
M 19639
 
4.2%
L 18458
 
4.0%
Other values (17) 106718
23.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 462858
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N 79491
17.2%
A 63721
13.8%
T 44082
9.5%
O 37890
 
8.2%
E 29552
 
6.4%
B 21834
 
4.7%
R 21834
 
4.7%
H 19639
 
4.2%
M 19639
 
4.2%
L 18458
 
4.0%
Other values (17) 106718
23.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 462858
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N 79491
17.2%
A 63721
13.8%
T 44082
9.5%
O 37890
 
8.2%
E 29552
 
6.4%
B 21834
 
4.7%
R 21834
 
4.7%
H 19639
 
4.2%
M 19639
 
4.2%
L 18458
 
4.0%
Other values (17) 106718
23.1%

x_coordinate_state_plane
Real number (ℝ)

High correlation  Missing 

Distinct20541
Distinct (%)35.8%
Missing1566
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean1001122.7
Minimum914084
Maximum1067128
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size460.4 KiB
2024-11-19T00:47:32.174653image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum914084
5-th percentile976433
Q1987769
median997470
Q31013515
95-th percentile1038929.2
Maximum1067128
Range153044
Interquartile range (IQR)25746

Descriptive statistics

Standard deviation21552.248
Coefficient of variation (CV)0.021528079
Kurtosis1.1354908
Mean1001122.7
Median Absolute Deviation (MAD)11185
Skewness0.0047316847
Sum5.7411382 × 1010
Variance4.644994 × 108
MonotonicityNot monotonic
2024-11-19T00:47:32.356167image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1035940 694
 
1.2%
946124 296
 
0.5%
998687 155
 
0.3%
1026862 91
 
0.2%
997787 88
 
0.1%
982367 82
 
0.1%
946097 77
 
0.1%
993651 75
 
0.1%
985799 69
 
0.1%
1017293 64
 
0.1%
Other values (20531) 55656
94.5%
(Missing) 1566
 
2.7%
ValueCountFrequency (%)
914084 2
< 0.1%
914381 1
 
< 0.1%
914616 4
< 0.1%
914856 1
 
< 0.1%
915031 2
< 0.1%
915092 1
 
< 0.1%
915172 3
< 0.1%
915191 1
 
< 0.1%
915252 1
 
< 0.1%
915470 1
 
< 0.1%
ValueCountFrequency (%)
1067128 1
 
< 0.1%
1066911 1
 
< 0.1%
1066626 2
< 0.1%
1066623 1
 
< 0.1%
1066615 1
 
< 0.1%
1066613 3
< 0.1%
1066604 1
 
< 0.1%
1066596 1
 
< 0.1%
1066589 2
< 0.1%
1066413 1
 
< 0.1%

y_coordinate_state_plane
Real number (ℝ)

High correlation  Missing 

Distinct22040
Distinct (%)38.4%
Missing1564
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean204170.52
Minimum121374
Maximum271861
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size460.4 KiB
2024-11-19T00:47:32.536918image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum121374
5-th percentile158344.8
Q1187605
median205155
Q3218497
95-th percentile250186.2
Maximum271861
Range150487
Interquartile range (IQR)30892

Descriptive statistics

Standard deviation26241.341
Coefficient of variation (CV)0.12852659
Kurtosis-0.17784387
Mean204170.52
Median Absolute Deviation (MAD)15484
Skewness-0.085459416
Sum1.1708975 × 1010
Variance6.8860797 × 108
MonotonicityNot monotonic
2024-11-19T00:47:32.705533image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
216775 694
 
1.2%
162287 300
 
0.5%
221604 146
 
0.2%
201883 92
 
0.2%
198444 88
 
0.1%
162281 77
 
0.1%
230741 75
 
0.1%
197857 71
 
0.1%
216568 69
 
0.1%
188272 66
 
0.1%
Other values (22030) 55671
94.5%
(Missing) 1564
 
2.7%
ValueCountFrequency (%)
121374 1
 
< 0.1%
124349 1
 
< 0.1%
124868 1
 
< 0.1%
125016 1
 
< 0.1%
125152 1
 
< 0.1%
125358 1
 
< 0.1%
125376 1
 
< 0.1%
125422 6
< 0.1%
125508 1
 
< 0.1%
125513 2
 
< 0.1%
ValueCountFrequency (%)
271861 4
< 0.1%
271054 1
 
< 0.1%
271005 2
 
< 0.1%
270768 3
 
< 0.1%
270176 1
 
< 0.1%
270038 1
 
< 0.1%
269885 2
 
< 0.1%
269699 1
 
< 0.1%
269605 8
< 0.1%
269588 2
 
< 0.1%
Distinct5
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size460.4 KiB
ONLINE
24195 
PHONE
21838 
MOBILE
12848 
UNKNOWN
 
28
OTHER
 
4

Length

Max length7
Median length6
Mean length5.6297252
Min length5

Characters and Unicode

Total characters331664
Distinct characters14
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPHONE
2nd rowPHONE
3rd rowPHONE
4th rowONLINE
5th rowMOBILE

Common Values

ValueCountFrequency (%)
ONLINE 24195
41.1%
PHONE 21838
37.1%
MOBILE 12848
21.8%
UNKNOWN 28
 
< 0.1%
OTHER 4
 
< 0.1%

Length

2024-11-19T00:47:32.888988image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-19T00:47:33.033627image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
online 24195
41.1%
phone 21838
37.1%
mobile 12848
21.8%
unknown 28
 
< 0.1%
other 4
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
N 70312
21.2%
O 58913
17.8%
E 58885
17.8%
L 37043
11.2%
I 37043
11.2%
H 21842
 
6.6%
P 21838
 
6.6%
M 12848
 
3.9%
B 12848
 
3.9%
U 28
 
< 0.1%
Other values (4) 64
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 331664
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N 70312
21.2%
O 58913
17.8%
E 58885
17.8%
L 37043
11.2%
I 37043
11.2%
H 21842
 
6.6%
P 21838
 
6.6%
M 12848
 
3.9%
B 12848
 
3.9%
U 28
 
< 0.1%
Other values (4) 64
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 331664
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N 70312
21.2%
O 58913
17.8%
E 58885
17.8%
L 37043
11.2%
I 37043
11.2%
H 21842
 
6.6%
P 21838
 
6.6%
M 12848
 
3.9%
B 12848
 
3.9%
U 28
 
< 0.1%
Other values (4) 64
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 331664
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N 70312
21.2%
O 58913
17.8%
E 58885
17.8%
L 37043
11.2%
I 37043
11.2%
H 21842
 
6.6%
P 21838
 
6.6%
M 12848
 
3.9%
B 12848
 
3.9%
U 28
 
< 0.1%
Other values (4) 64
 
< 0.1%

park_facility_name
Categorical

Imbalance 

Distinct11
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size460.4 KiB
Unspecified
58900 
MORRIS PARK BAKE SHOP
 
4
SALSA CON FUEGO
 
1
PARISI BAKERY
 
1
DJ REYNOLDS PUB AND RESTAURANT
 
1
Other values (6)
 
6

Length

Max length30
Median length11
Mean length11.001443
Min length7

Characters and Unicode

Total characters648128
Distinct characters33
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)< 0.1%

Sample

1st rowUnspecified
2nd rowUnspecified
3rd rowUnspecified
4th rowUnspecified
5th rowUnspecified

Common Values

ValueCountFrequency (%)
Unspecified 58900
> 99.9%
MORRIS PARK BAKE SHOP 4
 
< 0.1%
SALSA CON FUEGO 1
 
< 0.1%
PARISI BAKERY 1
 
< 0.1%
DJ REYNOLDS PUB AND RESTAURANT 1
 
< 0.1%
WENDY'S 1
 
< 0.1%
LE PAIN QUOTIDIEN 1
 
< 0.1%
MCDONALD'S 1
 
< 0.1%
HAI SUN RESTAURANT 1
 
< 0.1%
MASTER SMOOTHIE 1
 
< 0.1%

Length

2024-11-19T00:47:33.188213image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
unspecified 58900
99.9%
morris 4
 
< 0.1%
park 4
 
< 0.1%
bake 4
 
< 0.1%
shop 4
 
< 0.1%
restaurant 2
 
< 0.1%
salsa 1
 
< 0.1%
fuego 1
 
< 0.1%
parisi 1
 
< 0.1%
bakery 1
 
< 0.1%
Other values (17) 17
 
< 0.1%

Most occurring characters

ValueCountFrequency (%)
e 117800
18.2%
i 117800
18.2%
U 58906
9.1%
s 58900
9.1%
n 58900
9.1%
p 58900
9.1%
c 58900
9.1%
f 58900
9.1%
d 58900
9.1%
26
 
< 0.1%
Other values (23) 196
 
< 0.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 648128
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
e 117800
18.2%
i 117800
18.2%
U 58906
9.1%
s 58900
9.1%
n 58900
9.1%
p 58900
9.1%
c 58900
9.1%
f 58900
9.1%
d 58900
9.1%
26
 
< 0.1%
Other values (23) 196
 
< 0.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 648128
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
e 117800
18.2%
i 117800
18.2%
U 58906
9.1%
s 58900
9.1%
n 58900
9.1%
p 58900
9.1%
c 58900
9.1%
f 58900
9.1%
d 58900
9.1%
26
 
< 0.1%
Other values (23) 196
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 648128
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
e 117800
18.2%
i 117800
18.2%
U 58906
9.1%
s 58900
9.1%
n 58900
9.1%
p 58900
9.1%
c 58900
9.1%
f 58900
9.1%
d 58900
9.1%
26
 
< 0.1%
Other values (23) 196
 
< 0.1%

park_borough
Categorical

High correlation 

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size460.4 KiB
MANHATTAN
19639 
BROOKLYN
16056 
QUEENS
13575 
BRONX
5778 
STATEN ISLAND
2402 

Length

Max length13
Median length11
Mean length7.8566361
Min length5

Characters and Unicode

Total characters462858
Distinct characters27
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBROOKLYN
2nd rowBRONX
3rd rowMANHATTAN
4th rowBROOKLYN
5th rowBROOKLYN

Common Values

ValueCountFrequency (%)
MANHATTAN 19639
33.3%
BROOKLYN 16056
27.3%
QUEENS 13575
23.0%
BRONX 5778
 
9.8%
STATEN ISLAND 2402
 
4.1%
Unspecified 1463
 
2.5%

Length

2024-11-19T00:47:33.448518image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-11-19T00:47:33.593130image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
ValueCountFrequency (%)
manhattan 19639
32.0%
brooklyn 16056
26.2%
queens 13575
22.1%
bronx 5778
 
9.4%
staten 2402
 
3.9%
island 2402
 
3.9%
unspecified 1463
 
2.4%

Most occurring characters

ValueCountFrequency (%)
N 79491
17.2%
A 63721
13.8%
T 44082
9.5%
O 37890
 
8.2%
E 29552
 
6.4%
B 21834
 
4.7%
R 21834
 
4.7%
H 19639
 
4.2%
M 19639
 
4.2%
L 18458
 
4.0%
Other values (17) 106718
23.1%

Most occurring categories

ValueCountFrequency (%)
(unknown) 462858
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
N 79491
17.2%
A 63721
13.8%
T 44082
9.5%
O 37890
 
8.2%
E 29552
 
6.4%
B 21834
 
4.7%
R 21834
 
4.7%
H 19639
 
4.2%
M 19639
 
4.2%
L 18458
 
4.0%
Other values (17) 106718
23.1%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 462858
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
N 79491
17.2%
A 63721
13.8%
T 44082
9.5%
O 37890
 
8.2%
E 29552
 
6.4%
B 21834
 
4.7%
R 21834
 
4.7%
H 19639
 
4.2%
M 19639
 
4.2%
L 18458
 
4.0%
Other values (17) 106718
23.1%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 462858
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
N 79491
17.2%
A 63721
13.8%
T 44082
9.5%
O 37890
 
8.2%
E 29552
 
6.4%
B 21834
 
4.7%
R 21834
 
4.7%
H 19639
 
4.2%
M 19639
 
4.2%
L 18458
 
4.0%
Other values (17) 106718
23.1%

latitude
Real number (ℝ)

High correlation  Missing 

Distinct25732
Distinct (%)44.9%
Missing1569
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean40.727031
Minimum40.49957
Maximum40.912828
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size460.4 KiB
2024-11-19T00:47:33.763677image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum40.49957
5-th percentile40.601295
Q140.68154
median40.729744
Q340.766347
95-th percentile40.853346
Maximum40.912828
Range0.41325788
Interquartile range (IQR)0.084806712

Descriptive statistics

Standard deviation0.072026934
Coefficient of variation (CV)0.001768529
Kurtosis-0.17747501
Mean40.727031
Median Absolute Deviation (MAD)0.042470068
Skewness-0.085756609
Sum2335450.9
Variance0.0051878793
MonotonicityNot monotonic
2024-11-19T00:47:33.928277image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
40.76152265 694
 
1.2%
40.6120347 296
 
0.5%
40.77491631 146
 
0.2%
40.72069629 91
 
0.2%
40.71134933 88
 
0.1%
40.61201811 77
 
0.1%
40.80000172 75
 
0.1%
40.70974831 71
 
0.1%
40.76110546 69
 
0.1%
40.68337824 64
 
0.1%
Other values (25722) 55673
94.5%
(Missing) 1569
 
2.7%
ValueCountFrequency (%)
40.49956978 1
 
< 0.1%
40.50775363 1
 
< 0.1%
40.50914304 1
 
< 0.1%
40.50954848 1
 
< 0.1%
40.50992911 1
 
< 0.1%
40.51049806 1
 
< 0.1%
40.51054699 1
 
< 0.1%
40.51067378 6
< 0.1%
40.51091083 1
 
< 0.1%
40.51092453 2
 
< 0.1%
ValueCountFrequency (%)
40.91282765 4
< 0.1%
40.91060759 1
 
< 0.1%
40.91047872 1
 
< 0.1%
40.91047309 1
 
< 0.1%
40.90982838 3
< 0.1%
40.90820392 1
 
< 0.1%
40.90782747 1
 
< 0.1%
40.90740538 2
< 0.1%
40.90689522 1
 
< 0.1%
40.90659041 2
< 0.1%

longitude
Real number (ℝ)

High correlation  Missing 

Distinct25732
Distinct (%)44.9%
Missing1569
Missing (%)2.7%
Infinite0
Infinite (%)0.0%
Mean-73.939096
Minimum-74.252343
Maximum-73.700929
Zeros0
Zeros (%)0.0%
Negative57344
Negative (%)97.3%
Memory size460.4 KiB
2024-11-19T00:47:34.082821image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Quantile statistics

Minimum-74.252343
5-th percentile-74.028162
Q1-73.987303
median-73.952337
Q3-73.894381
95-th percentile-73.802681
Maximum-73.700929
Range0.55141369
Interquartile range (IQR)0.092922131

Descriptive statistics

Standard deviation0.0777343
Coefficient of variation (CV)-0.0010513288
Kurtosis1.1247575
Mean-73.939096
Median Absolute Deviation (MAD)0.040367762
Skewness0.0074441299
Sum-4239963.5
Variance0.0060426214
MonotonicityNot monotonic
2024-11-19T00:47:34.253365image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-73.81341016 694
 
1.2%
-74.13731846 296
 
0.5%
-73.94787507 146
 
0.2%
-73.84627407 91
 
0.2%
-73.95117114 88
 
0.1%
-74.13741567 77
 
0.1%
-73.96604481 75
 
0.1%
-74.00679194 71
 
0.1%
-73.99440848 69
 
0.1%
-73.88086167 64
 
0.1%
Other values (25722) 55673
94.5%
(Missing) 1569
 
2.7%
ValueCountFrequency (%)
-74.25234297 2
< 0.1%
-74.2512771 1
 
< 0.1%
-74.25043315 4
< 0.1%
-74.24956219 1
 
< 0.1%
-74.24893041 2
< 0.1%
-74.24871018 1
 
< 0.1%
-74.24843668 3
< 0.1%
-74.24836242 1
 
< 0.1%
-74.24814344 1
 
< 0.1%
-74.24734551 1
 
< 0.1%
ValueCountFrequency (%)
-73.70092928 1
 
< 0.1%
-73.70171308 1
 
< 0.1%
-73.70268276 2
< 0.1%
-73.70269361 1
 
< 0.1%
-73.70272256 1
 
< 0.1%
-73.7027297 3
< 0.1%
-73.70276236 1
 
< 0.1%
-73.70279129 1
 
< 0.1%
-73.70281653 2
< 0.1%
-73.70351185 1
 
< 0.1%

location
Text

Missing 

Distinct25732
Distinct (%)44.9%
Missing1569
Missing (%)2.7%
Memory size460.4 KiB
2024-11-19T00:47:34.579500image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Length

Max length141
Median length140
Mean length140.06805
Min length136

Characters and Unicode

Total characters8032062
Distinct characters38
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15005 ?
Unique (%)26.2%

Sample

1st row{'latitude': '40.577479337191384', 'longitude': '-73.9620829225648', 'human_address': '{"address": "", "city": "", "state": "", "zip": ""}'}
2nd row{'latitude': '40.8558288801221', 'longitude': '-73.85555931275691', 'human_address': '{"address": "", "city": "", "state": "", "zip": ""}'}
3rd row{'latitude': '40.74758418018265', 'longitude': '-73.9864914082603', 'human_address': '{"address": "", "city": "", "state": "", "zip": ""}'}
4th row{'latitude': '40.71827775344117', 'longitude': '-73.959946580784', 'human_address': '{"address": "", "city": "", "state": "", "zip": ""}'}
5th row{'latitude': '40.59326974931518', 'longitude': '-73.9607993127448', 'human_address': '{"address": "", "city": "", "state": "", "zip": ""}'}
ValueCountFrequency (%)
229376
30.8%
latitude 57344
 
7.7%
longitude 57344
 
7.7%
human_address 57344
 
7.7%
state 57344
 
7.7%
address 57344
 
7.7%
city 57344
 
7.7%
zip 57344
 
7.7%
73.81341016404748 694
 
0.1%
40.76152264872703 694
 
0.1%
Other values (51462) 113300
15.2%
2024-11-19T00:47:35.056257image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
" 917504
 
11.4%
' 688128
 
8.6%
688128
 
8.6%
: 401408
 
5.0%
d 344064
 
4.3%
t 344064
 
4.3%
, 286720
 
3.6%
e 286720
 
3.6%
s 286720
 
3.6%
a 286720
 
3.6%
Other values (28) 3501886
43.6%

Most occurring categories

ValueCountFrequency (%)
(unknown) 8032062
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
" 917504
 
11.4%
' 688128
 
8.6%
688128
 
8.6%
: 401408
 
5.0%
d 344064
 
4.3%
t 344064
 
4.3%
, 286720
 
3.6%
e 286720
 
3.6%
s 286720
 
3.6%
a 286720
 
3.6%
Other values (28) 3501886
43.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 8032062
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
" 917504
 
11.4%
' 688128
 
8.6%
688128
 
8.6%
: 401408
 
5.0%
d 344064
 
4.3%
t 344064
 
4.3%
, 286720
 
3.6%
e 286720
 
3.6%
s 286720
 
3.6%
a 286720
 
3.6%
Other values (28) 3501886
43.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 8032062
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
" 917504
 
11.4%
' 688128
 
8.6%
688128
 
8.6%
: 401408
 
5.0%
d 344064
 
4.3%
t 344064
 
4.3%
, 286720
 
3.6%
e 286720
 
3.6%
s 286720
 
3.6%
a 286720
 
3.6%
Other values (28) 3501886
43.6%

closed_date
Date

Missing 

Distinct49129
Distinct (%)94.4%
Missing6875
Missing (%)11.7%
Memory size460.4 KiB
Minimum2019-01-25 10:20:32
Maximum2024-09-23 12:59:03
2024-11-19T00:47:35.225354image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:47:35.415843image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

resolution_description
Categorical

High correlation  Imbalance  Missing 

Distinct15
Distinct (%)< 0.1%
Missing5769
Missing (%)9.8%
Memory size460.4 KiB
This SR was administratively closed. The issue you reported was addressed.
49035 
The Department of Health and Mental Hygiene has sent official written notification to the Owner/Landlord warning them of potential violations and instructing them to correct the situation. If the situation persists 21 days after your initial complaint, please make a new complaint.
 
2121
The Department of Health and Mental Hygiene has sent official written notification to the Owner/Landlord warning them of potential violations and instructing them to correct the situation. If the situation persists 21 days after your initial complaint, please make a new complaint.
 
1518
The Department of Health and Mental Hygiene has reviewed your Service Request. A warning letter has been sent to the responsible party notifying them to correct the condition. An inspector will be dispatched if needed. If the condition persists 21 days after the initial report, please call 311 to file another Service Request.
 
398
The Department of Health and Mental Hygiene has sent an official warning to the establishment. If the situation persists 45 days after the initial report, call 311 and file a new Service Reqeust.
 
28
Other values (10)
 
44

Length

Max length495
Median length74
Mean length90.328899
Min length74

Characters and Unicode

Total characters4800439
Distinct characters55
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)< 0.1%

Sample

1st rowThis SR was administratively closed. The issue you reported was addressed.
2nd rowThe Department of Health and Mental Hygiene has sent official written notification to the Owner/Landlord warning them of potential violations and instructing them to correct the situation. If the situation persists 21 days after your initial complaint, please make a new complaint.
3rd rowThe Department of Health and Mental Hygiene has sent official written notification to the Owner/Landlord warning them of potential violations and instructing them to correct the situation. If the situation persists 21 days after your initial complaint, please make a new complaint.
4th rowThe Department of Health and Mental Hygiene has sent official written notification to the Owner/Landlord warning them of potential violations and instructing them to correct the situation. If the situation persists 21 days after your initial complaint, please make a new complaint.
5th rowThe Department of Health and Mental Hygiene has sent official written notification to the Owner/Landlord warning them of potential violations and instructing them to correct the situation. If the situation persists 21 days after your initial complaint, please make a new complaint.

Common Values

ValueCountFrequency (%)
This SR was administratively closed. The issue you reported was addressed. 49035
83.2%
The Department of Health and Mental Hygiene has sent official written notification to the Owner/Landlord warning them of potential violations and instructing them to correct the situation. If the situation persists 21 days after your initial complaint, please make a new complaint. 2121
 
3.6%
The Department of Health and Mental Hygiene has sent official written notification to the Owner/Landlord warning them of potential violations and instructing them to correct the situation. If the situation persists 21 days after your initial complaint, please make a new complaint. 1518
 
2.6%
The Department of Health and Mental Hygiene has reviewed your Service Request. A warning letter has been sent to the responsible party notifying them to correct the condition. An inspector will be dispatched if needed. If the condition persists 21 days after the initial report, please call 311 to file another Service Request. 398
 
0.7%
The Department of Health and Mental Hygiene has sent an official warning to the establishment. If the situation persists 45 days after the initial report, call 311 and file a new Service Reqeust. 28
 
< 0.1%
The Department of Health and Mental Hygiene regulates restaurants and other establishments that mostly sell food which is prepared on the premises. New York State Agriculture and Markets regulates those establishments that mostly sell pre-packaged food, including supermarkets, bodegas, green markets, fish and meat markets, and delis. This Service Request involves an establishment under the jurisdiction of the New York State Agriculture and Markets. For complaint status, call (718) 722-2876. 13
 
< 0.1%
The Department of Health and Mental Hygiene has determined that this issue is not within its jurisdiction; it cannot be determined if another agency would regulate the issue reported. This Service Request has been closed. 10
 
< 0.1%
The Department of Health and Mental Hygiene has investigated the complaint. No violations were cited and no further action will be taken. 7
 
< 0.1%
The Department of Health and Mental Hygiene has investigated the complaint. No violations were cited and no further action will be taken. 5
 
< 0.1%
The Department of Health and Mental Hygiene has investigated the complaint and issued a Notice of Violation. No further action will be taken. 2
 
< 0.1%
Other values (5) 7
 
< 0.1%
(Missing) 5769
 
9.8%

Length

2024-11-19T00:47:35.596364image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
was 98072
13.7%
the 65816
9.2%
this 49068
 
6.9%
issue 49055
 
6.9%
closed 49048
 
6.9%
reported 49045
 
6.9%
administratively 49035
 
6.8%
sr 49035
 
6.8%
you 49035
 
6.8%
addressed 49035
 
6.8%
Other values (116) 159724
22.3%

Most occurring characters

ValueCountFrequency (%)
664955
13.9%
e 495432
 
10.3%
s 487857
 
10.2%
i 338213
 
7.0%
a 332442
 
6.9%
d 316448
 
6.6%
t 272980
 
5.7%
r 243640
 
5.1%
o 215543
 
4.5%
n 141707
 
3.0%
Other values (45) 1291222
26.9%

Most occurring categories

ValueCountFrequency (%)
(unknown) 4800439
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
664955
13.9%
e 495432
 
10.3%
s 487857
 
10.2%
i 338213
 
7.0%
a 332442
 
6.9%
d 316448
 
6.6%
t 272980
 
5.7%
r 243640
 
5.1%
o 215543
 
4.5%
n 141707
 
3.0%
Other values (45) 1291222
26.9%

Most occurring scripts

ValueCountFrequency (%)
(unknown) 4800439
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
664955
13.9%
e 495432
 
10.3%
s 487857
 
10.2%
i 338213
 
7.0%
a 332442
 
6.9%
d 316448
 
6.6%
t 272980
 
5.7%
r 243640
 
5.1%
o 215543
 
4.5%
n 141707
 
3.0%
Other values (45) 1291222
26.9%

Most occurring blocks

ValueCountFrequency (%)
(unknown) 4800439
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
664955
13.9%
e 495432
 
10.3%
s 487857
 
10.2%
i 338213
 
7.0%
a 332442
 
6.9%
d 316448
 
6.6%
t 272980
 
5.7%
r 243640
 
5.1%
o 215543
 
4.5%
n 141707
 
3.0%
Other values (45) 1291222
26.9%
Distinct37308
Distinct (%)70.2%
Missing5769
Missing (%)9.8%
Memory size460.4 KiB
Minimum2019-01-25 10:20:32
Maximum2024-09-23 12:59:05
2024-11-19T00:47:35.752942image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:47:35.941437image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

due_date
Date

Missing 

Distinct5235
Distinct (%)> 99.9%
Missing53677
Missing (%)91.1%
Memory size460.4 KiB
Minimum2019-01-25 09:31:31
Maximum2019-08-26 15:46:45
2024-11-19T00:47:36.119564image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:47:36.311003image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

facility_type
Unsupported

Missing  Rejected  Unsupported 

Missing58913
Missing (%)100.0%
Memory size460.4 KiB

Interactions

2024-11-19T00:29:02.191953image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:05:18.414934image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:07:10.496809image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:09:41.714051image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:12:55.123841image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:17:05.695221image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:22:30.417026image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:30:04.656983image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:05:31.807199image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:07:29.668417image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:10:06.369374image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:13:27.343748image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:17:47.070593image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:23:21.917591image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:31:08.527834image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:05:45.885931image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:07:49.355307image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:10:32.342008image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:14:00.604318image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:18:29.848139image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:24:15.359281image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:32:13.410524image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:06:00.414912image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:08:10.154114image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:10:58.888229image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:14:34.324951image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:19:16.005770image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:25:09.822526image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:33:20.062405image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:06:16.555425image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:08:31.725001image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:11:26.409913image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:15:10.223319image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:20:04.223520image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:26:05.964080image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:34:28.969624image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:06:34.070270image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:08:54.060955image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:11:54.709436image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:15:47.332955image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:20:51.498215image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:27:03.109169image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:35:39.182935image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:06:52.305441image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:09:17.543675image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:12:24.479400image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:16:26.140877image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:21:40.061026image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
2024-11-19T00:28:01.957186image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/

Correlations

2024-11-19T00:47:36.465591image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
address_typebblboroughdescriptorincident_ziplatitudelocation_typelongitudeopen_data_channel_typepark_boroughpark_facility_nameresolution_descriptionstatusunique_keyx_coordinate_state_planey_coordinate_state_plane
address_type1.0000.1000.0150.0650.0410.0290.0660.0260.1220.0150.0000.1100.0370.1650.0260.029
bbl0.1001.0000.8940.0690.842-0.4120.0210.4960.0730.8940.0000.0080.031-0.0460.496-0.411
borough0.0150.8941.0000.0920.6850.5610.0290.6090.1171.0000.0050.0290.0380.0930.6090.562
descriptor0.0650.0690.0921.0000.0740.0620.0740.0670.1970.0920.0000.0910.0820.0980.0670.062
incident_zip0.0410.8420.6850.0741.000-0.3740.0250.6240.0730.6850.0000.0090.027-0.0210.625-0.374
latitude0.029-0.4120.5610.062-0.3741.0000.0220.3260.0720.5610.0000.0140.0270.0100.3251.000
location_type0.0660.0210.0290.0740.0250.0221.0000.0320.1490.0290.0110.0520.0490.2040.0320.022
longitude0.0260.4960.6090.0670.6240.3260.0321.0000.0820.6090.0000.0090.034-0.0201.0000.326
open_data_channel_type0.1220.0730.1170.1970.0730.0720.1490.0821.0000.1170.0000.0400.0390.0950.0810.072
park_borough0.0150.8941.0000.0920.6850.5610.0290.6090.1171.0000.0050.0290.0380.0930.6090.562
park_facility_name0.0000.0000.0050.0000.0000.0000.0110.0000.0000.0051.0000.0000.0000.0060.0000.000
resolution_description0.1100.0080.0290.0910.0090.0140.0520.0090.0400.0290.0001.0000.6010.2820.0090.014
status0.0370.0310.0380.0820.0270.0270.0490.0340.0390.0380.0000.6011.0000.6530.0340.027
unique_key0.165-0.0460.0930.098-0.0210.0100.204-0.0200.0950.0930.0060.2820.6531.000-0.0200.010
x_coordinate_state_plane0.0260.4960.6090.0670.6250.3250.0321.0000.0810.6090.0000.0090.034-0.0201.0000.326
y_coordinate_state_plane0.029-0.4110.5620.062-0.3741.0000.0220.3260.0720.5620.0000.0140.0270.0100.3261.000

Missing values

2024-11-19T00:36:51.115258image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-11-19T00:38:05.164543image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-11-19T00:39:20.799512image/svg+xmlMatplotlib v3.9.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

unique_keycreated_dateagencyagency_namecomplaint_typedescriptorlocation_typeincident_zipincident_addressstreet_namecross_street_1cross_street_2intersection_street_1intersection_street_2address_typecitylandmarkstatuscommunity_boardbblboroughx_coordinate_state_planey_coordinate_state_planeopen_data_channel_typepark_facility_namepark_boroughlatitudelongitudelocationclosed_dateresolution_descriptionresolution_action_updated_datedue_datefacility_type
0626055712024-09-29T23:42:42.000DOHMHDepartment of Health and Mental HygieneFood EstablishmentBare Hands in Contact w/ FoodRestaurant/Bar/Deli/Bakery11235.0523 BRIGHTON BEACH AVENUEBRIGHTON BEACH AVENUEBRIGHTON 5 STREETBRIGHTON 6 STREETBRIGHTON 5 STREETBRIGHTON 6 STREETADDRESSBROOKLYNBRIGHTON BEACH AVENUEIn Progress13 BROOKLYN3.086750e+09BROOKLYN994783.0149670.0PHONEUnspecifiedBROOKLYN40.577479-73.962083{'latitude': '40.577479337191384', 'longitude': '-73.9620829225648', 'human_address': '{"address": "", "city": "", "state": "", "zip": ""}'}NaNNaNNaNNaNNaN
1626019362024-09-29T21:52:07.000DOHMHDepartment of Health and Mental HygieneFood EstablishmentRodents/Insects/GarbageRestaurant/Bar/Deli/Bakery10461.02117 WILLIAMBRIDGE ROADWILLIAMBRIDGE ROADLYDIG AVENUEPELHAM PARKWAY SOUTHLYDIG AVENUEPELHAM PARKWAY SOUTHADDRESSBRONXWILLIAMSBRIDGE ROADIn Progress11 BRONX2.043320e+09BRONX1024207.0251112.0PHONEUnspecifiedBRONX40.855829-73.855559{'latitude': '40.8558288801221', 'longitude': '-73.85555931275691', 'human_address': '{"address": "", "city": "", "state": "", "zip": ""}'}NaNNaNNaNNaNNaN
2626027352024-09-29T21:22:45.000DOHMHDepartment of Health and Mental HygieneFood EstablishmentRodents/Insects/GarbageRestaurant/Bar/Deli/Bakery10001.031 WEST 32 STREETWEST 32 STREET5 AVENUEBROADWAY5 AVENUEBROADWAYADDRESSNEW YORKWEST 32 STREETIn Progress05 MANHATTAN1.008340e+09MANHATTAN987993.0211642.0PHONEUnspecifiedMANHATTAN40.747584-73.986491{'latitude': '40.74758418018265', 'longitude': '-73.9864914082603', 'human_address': '{"address": "", "city": "", "state": "", "zip": ""}'}NaNNaNNaNNaNNaN
3626055002024-09-29T21:14:24.000DOHMHDepartment of Health and Mental HygieneFood EstablishmentRodents/Insects/GarbageRestaurant/Bar/Deli/BakeryNaN114NaNBERRY STREMIKE LEEBERRY STREMIKE LEENaNBrooklynNaNIn ProgressUnspecified BROOKLYN3.023340e+09BROOKLYN995353.0200967.0ONLINEUnspecifiedBROOKLYN40.718278-73.959947{'latitude': '40.71827775344117', 'longitude': '-73.959946580784', 'human_address': '{"address": "", "city": "", "state": "", "zip": ""}'}NaNNaNNaNNaNNaN
4626036352024-09-29T21:05:25.000DOHMHDepartment of Health and Mental HygieneFood EstablishmentBare Hands in Contact w/ FoodRestaurant/Bar/Deli/Bakery11223.02605 CONEY ISLAND AVENUECONEY ISLAND AVENUEAVENUE WLANCASTER AVENUEAVENUE WLANCASTER AVENUEADDRESSBROOKLYNCONEY ISLAND AVENUEIn Progress15 BROOKLYN3.073940e+09BROOKLYN995137.0155423.0MOBILEUnspecifiedBROOKLYN40.593270-73.960799{'latitude': '40.59326974931518', 'longitude': '-73.9607993127448', 'human_address': '{"address": "", "city": "", "state": "", "zip": ""}'}NaNNaNNaNNaNNaN
5626038052024-09-29T19:26:50.000DOHMHDepartment of Health and Mental HygieneFood EstablishmentRodents/Insects/GarbageRestaurant/Bar/Deli/Bakery11215.0192 PROSPECT PARK WESTPROSPECT PARK WESTNaN15 STREETNaN15 STREETADDRESSBROOKLYNPROSPECT PARK WESTIn Progress06 BROOKLYN3.011030e+09BROOKLYN989873.0180198.0MOBILEUnspecifiedBROOKLYN40.661277-73.979733{'latitude': '40.661276811907456', 'longitude': '-73.9797326921662', 'human_address': '{"address": "", "city": "", "state": "", "zip": ""}'}NaNNaNNaNNaNNaN
6626027342024-09-29T19:16:42.000DOHMHDepartment of Health and Mental HygieneFood EstablishmentNo Permit or LicenseRestaurant/Bar/Deli/Bakery11417.093-10 LIBERTY AVENUELIBERTY AVENUE93 STREET94 STREET93 STREET94 STREETADDRESSOZONE PARKLIBERTY AVENUEIn Progress10 QUEENS4.091620e+09QUEENS1027054.0187128.0MOBILEUnspecifiedQUEENS40.680196-73.845675{'latitude': '40.68019640487362', 'longitude': '-73.84567519025673', 'human_address': '{"address": "", "city": "", "state": "", "zip": ""}'}NaNNaNNaNNaNNaN
7626020052024-09-29T17:55:03.000DOHMHDepartment of Health and Mental HygieneFood EstablishmentRodents/Insects/GarbageRestaurant/Bar/Deli/Bakery10014.0567 HUDSON STREETHUDSON STREETPERRY STREETWEST 11 STREETPERRY STREETWEST 11 STREETADDRESSNEW YORKHUDSON STREETIn Progress02 MANHATTAN1.006330e+09MANHATTAN982591.0207327.0ONLINEUnspecifiedMANHATTAN40.735741-74.005986{'latitude': '40.73574121648932', 'longitude': '-74.00598631322032', 'human_address': '{"address": "", "city": "", "state": "", "zip": ""}'}NaNNaNNaNNaNNaN
8626064932024-09-29T17:43:04.000DOHMHDepartment of Health and Mental HygieneFood EstablishmentToilet FacilityRestaurant/Bar/Deli/Bakery11209.09243 4 AVENUE4 AVENUE93 STREET94 STREET93 STREET94 STREETADDRESSBROOKLYN4 AVENUEIn Progress10 BROOKLYN3.061080e+09BROOKLYN975770.0164215.0PHONEUnspecifiedBROOKLYN40.617405-74.030545{'latitude': '40.61740462322561', 'longitude': '-74.03054487148385', 'human_address': '{"address": "", "city": "", "state": "", "zip": ""}'}NaNNaNNaNNaNNaN
9626042472024-09-29T16:43:02.000DOHMHDepartment of Health and Mental HygieneFood EstablishmentFood ContaminatedRestaurant/Bar/Deli/Bakery10038.0164 WILLIAM STREETWILLIAM STREETANN STREETBEEKMAN STREETANN STREETBEEKMAN STREETADDRESSNEW YORKWILLIAM STREETIn Progress01 MANHATTAN1.000930e+09MANHATTAN982655.0198034.0ONLINEUnspecifiedMANHATTAN40.710234-74.005753{'latitude': '40.71023419230766', 'longitude': '-74.00575317413539', 'human_address': '{"address": "", "city": "", "state": "", "zip": ""}'}NaNNaNNaNNaNNaN
unique_keycreated_dateagencyagency_namecomplaint_typedescriptorlocation_typeincident_zipincident_addressstreet_namecross_street_1cross_street_2intersection_street_1intersection_street_2address_typecitylandmarkstatuscommunity_boardbblboroughx_coordinate_state_planey_coordinate_state_planeopen_data_channel_typepark_facility_namepark_boroughlatitudelongitudelocationclosed_dateresolution_descriptionresolution_action_updated_datedue_datefacility_type
58903413180012019-01-01T12:57:21.000DOHMHDepartment of Health and Mental HygieneFood EstablishmentLetter GradingRestaurant/Bar/Deli/Bakery10309.04864 ARTHUR KIL ROADARTHUR KIL ROADSOUTH BRIDGE STREETRICHMOND VALLEY ROADNaNNaNADDRESSSTATEN ISLANDNaNClosed03 STATEN ISLAND5.075840e+09STATEN ISLAND917747.0130119.0PHONEUnspecifiedSTATEN ISLAND40.523573-74.239207{'latitude': '40.5235725885887', 'longitude': '-74.23920715187802', 'human_address': '{"address": "", "city": "", "state": "", "zip": ""}'}2019-03-03T06:18:15.000The Department of Health and Mental Hygiene has sent official written notification to the Owner/Landlord warning them of potential violations and instructing them to correct the situation. If the situation persists 21 days after your initial complaint, please make a new complaint.2019-03-03T06:18:16.0002019-03-02T12:57:21.000NaN
58904413149822019-01-01T12:18:43.000DOHMHDepartment of Health and Mental HygieneFood EstablishmentFood SpoiledRestaurant/Bar/Deli/Bakery11368.096-23 57 AVENUE57 AVENUE96 STREET97 STREETNaNNaNADDRESSCORONANaNClosed04 QUEENS4.019040e+09QUEENS1021789.0207822.0PHONEUnspecifiedQUEENS40.737020-73.864542{'latitude': '40.73702035936368', 'longitude': '-73.86454212450096', 'human_address': '{"address": "", "city": "", "state": "", "zip": ""}'}2019-03-03T06:18:16.000The Department of Health and Mental Hygiene has sent official written notification to the Owner/Landlord warning them of potential violations and instructing them to correct the situation. If the situation persists 21 days after your initial complaint, please make a new complaint.2019-03-03T06:18:16.0002019-03-02T12:18:43.000NaN
58905413164492019-01-01T11:32:20.000DOHMHDepartment of Health and Mental HygieneFood EstablishmentRodents/Insects/GarbageRestaurant/Bar/Deli/Bakery11373.077-00 QUEENS BOULEVARDQUEENS BOULEVARDIRELAND STREETALBION AVENUENaNNaNADDRESSELMHURSTNaNClosed04 QUEENS4.024520e+09QUEENS1015767.0208332.0PHONEUnspecifiedQUEENS40.738444-73.886270{'latitude': '40.73844369159779', 'longitude': '-73.88626983778089', 'human_address': '{"address": "", "city": "", "state": "", "zip": ""}'}2019-03-03T06:18:17.000The Department of Health and Mental Hygiene has sent official written notification to the Owner/Landlord warning them of potential violations and instructing them to correct the situation. If the situation persists 21 days after your initial complaint, please make a new complaint.2019-03-03T06:18:17.0002019-03-02T11:32:20.000NaN
58906413189742019-01-01T11:06:20.000DOHMHDepartment of Health and Mental HygieneFood EstablishmentHandwashingOther (Explain Below)11217.0576 ATLANTIC AVENUEATLANTIC AVENUE3 AVENUE4 AVENUE3 AVENUE4 AVENUEADDRESSBROOKLYNNaNClosed02 BROOKLYN3.001860e+09BROOKLYN990116.0188693.0PHONEUnspecifiedBROOKLYN40.684594-73.978849{'latitude': '40.684593521742336', 'longitude': '-73.97884944004804', 'human_address': '{"address": "", "city": "", "state": "", "zip": ""}'}2024-06-03T10:07:59.000This SR was administratively closed. The issue you reported was addressed.2024-06-03T10:08:06.0002019-02-07T11:06:20.000NaN
58907413175662019-01-01T10:50:27.000DOHMHDepartment of Health and Mental HygieneFood EstablishmentRodents/Insects/GarbageRestaurant/Bar/Deli/Bakery11215.0225 7 AVENUE7 AVENUE3 STREET4 STREETNaNNaNADDRESSBROOKLYNNaNClosed06 BROOKLYN3.010800e+09BROOKLYN990092.0183390.0ONLINEUnspecifiedBROOKLYN40.670038-73.978941{'latitude': '40.67003800101288', 'longitude': '-73.9789405717176', 'human_address': '{"address": "", "city": "", "state": "", "zip": ""}'}2019-03-03T06:18:15.000The Department of Health and Mental Hygiene has sent official written notification to the Owner/Landlord warning them of potential violations and instructing them to correct the situation. If the situation persists 21 days after your initial complaint, please make a new complaint.2019-03-03T06:18:15.0002019-03-02T10:50:27.000NaN
58908413164202019-01-01T10:40:40.000DOHMHDepartment of Health and Mental HygieneFood EstablishmentRodents/Insects/GarbageRestaurant/Bar/Deli/Bakery10014.075 GREENWICH AVENUEGREENWICH AVENUE7 AVENUEBANK STREETNaNNaNADDRESSNEW YORKNaNClosed02 MANHATTAN1.006140e+09MANHATTAN983917.0207684.0ONLINEUnspecifiedMANHATTAN40.736721-74.001202{'latitude': '40.73672124264221', 'longitude': '-74.0012016103804', 'human_address': '{"address": "", "city": "", "state": "", "zip": ""}'}2019-03-03T06:18:17.000The Department of Health and Mental Hygiene has sent official written notification to the Owner/Landlord warning them of potential violations and instructing them to correct the situation. If the situation persists 21 days after your initial complaint, please make a new complaint.2019-03-03T06:18:17.0002019-03-02T10:40:40.000NaN
58909413181192019-01-01T09:56:59.000DOHMHDepartment of Health and Mental HygieneFood EstablishmentPet/AnimalRestaurant/Bar/Deli/Bakery11226.01603 CORTELYOU ROADCORTELYOU ROADEAST 16 STREETEAST 17 STREETNaNNaNADDRESSBROOKLYNNaNClosed14 BROOKLYN3.051470e+09BROOKLYN994404.0173061.0ONLINEUnspecifiedBROOKLYN40.641683-73.963412{'latitude': '40.64168326471781', 'longitude': '-73.96341208990378', 'human_address': '{"address": "", "city": "", "state": "", "zip": ""}'}2019-03-03T06:18:17.000The Department of Health and Mental Hygiene has sent official written notification to the Owner/Landlord warning them of potential violations and instructing them to correct the situation. If the situation persists 21 days after your initial complaint, please make a new complaint.2019-03-03T06:18:17.0002019-03-02T09:56:59.000NaN
58910413147912019-01-01T08:38:30.000DOHMHDepartment of Health and Mental HygieneFood EstablishmentToilet FacilityRestaurant/Bar/Deli/Bakery10022.01066 2 AVENUE2 AVENUEEAST 56 STREETEAST 57 STREETNaNNaNADDRESSNEW YORKNaNClosed06 MANHATTAN1.013490e+09MANHATTAN993752.0215704.0ONLINEUnspecifiedMANHATTAN40.758729-73.965701{'latitude': '40.758729026402136', 'longitude': '-73.96570127751059', 'human_address': '{"address": "", "city": "", "state": "", "zip": ""}'}2019-03-03T06:18:17.000The Department of Health and Mental Hygiene has sent official written notification to the Owner/Landlord warning them of potential violations and instructing them to correct the situation. If the situation persists 21 days after your initial complaint, please make a new complaint.2019-03-03T06:18:17.0002019-03-02T08:38:30.000NaN
58911413150102019-01-01T07:59:30.000DOHMHDepartment of Health and Mental HygieneFood EstablishmentLetter GradingRestaurant/Bar/Deli/Bakery10466.04045 LACONIA AVENUELACONIA AVENUEEAST 227 STREETEAST 228 STREETNaNNaNADDRESSBRONXNaNClosed12 BRONX2.048740e+09BRONX1026284.0262179.0ONLINEUnspecifiedBRONX40.886195-73.847982{'latitude': '40.88619471722822', 'longitude': '-73.8479817460043', 'human_address': '{"address": "", "city": "", "state": "", "zip": ""}'}2019-03-03T06:18:17.000The Department of Health and Mental Hygiene has sent official written notification to the Owner/Landlord warning them of potential violations and instructing them to correct the situation. If the situation persists 21 days after your initial complaint, please make a new complaint.2019-03-03T06:18:17.0002019-03-02T07:59:30.000NaN
58912413072362019-01-01T01:17:04.000DOHMHDepartment of Health and Mental HygieneFood EstablishmentKitchen/Food Prep AreaRestaurant/Bar/Deli/Bakery11212.09323 CHURCH AVENUECHURCH AVENUELINDEN BOULEVARDEAST 94 STREETNaNNaNADDRESSBROOKLYNNaNClosed17 BROOKLYN3.046900e+09BROOKLYN1007207.0177753.0ONLINEUnspecifiedBROOKLYN40.654538-73.917263{'latitude': '40.654537851407625', 'longitude': '-73.91726308878049', 'human_address': '{"address": "", "city": "", "state": "", "zip": ""}'}2019-03-02T06:18:22.000The Department of Health and Mental Hygiene has sent official written notification to the Owner/Landlord warning them of potential violations and instructing them to correct the situation. If the situation persists 21 days after your initial complaint, please make a new complaint.2019-03-02T06:18:22.0002019-03-02T01:17:04.000NaN